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social-media-analytics
Advanced tools
MCP server for social media analytics - profile analysis, hashtag research, content calendars, competitor analysis, and viral scoring
An MCP (Model Context Protocol) server for social media analysis and marketing optimization. Analyze profiles, research hashtags, generate content calendars, benchmark competitors, and score content for viral potential -- all from your AI assistant.
| Plan | Price | Features |
|---|---|---|
| Basic | $10/mo | Profile analysis, hashtag research, viral scoring — Buy → |
| Pro | $15/mo | Everything in Basic + content calendars, competitor analysis, priority support — Buy → |
Free trial: 3 calls total (shared across all tools), no credit card. License keys are emailed instantly after checkout. Activate via the LICENSE_KEY environment variable. More info: aivp-mcp.vercel.app
No install step needed — run straight from npm:
npx -y social-media-analytics
Or install globally:
npm install -g social-media-analytics
Add to your claude_desktop_config.json:
{
"mcpServers": {
"social-media-analytics": {
"command": "npx",
"args": ["-y", "social-media-analytics"],
"env": { "LICENSE_KEY": "<your license key — omit for free trial>" }
}
}
}
claude mcp add social-media-analytics -- npx -y social-media-analytics
# Start the SSE server (default port 3000)
npx -y social-media-analytics --sse
# Or specify a custom port
PORT=8080 npx -y social-media-analytics --sse
The Streamable HTTP endpoint is available at http://localhost:3000/mcp.
analyze_profileAnalyze a social media profile from its URL. Extracts publicly available data including profile name, bio, follower count, post frequency, engagement rate, and content themes.
Input:
{
"url": "https://twitter.com/elonmusk"
}
Supported platforms: Twitter/X, Instagram, YouTube, LinkedIn, TikTok
analyze_hashtagsAnalyze hashtags for estimated popularity, related tags, best posting times, competition level, and platform-specific recommendations.
Input:
{
"hashtags": ["#ai", "#startup", "#buildinpublic"],
"platforms": ["twitter", "linkedin"]
}
generate_content_calendarGenerate a 30-day content calendar with post ideas, captions, optimal posting times, content mix recommendations, and hashtag suggestions.
Input:
{
"niche": "AI startups",
"platforms": ["twitter", "linkedin", "instagram"],
"posts_per_week": 5
}
analyze_competitorsCompare 2-5 competitor profiles side-by-side with follower comparison, content strategy analysis, posting frequency, and engagement benchmarks.
Input:
{
"competitors": [
"https://twitter.com/competitor1",
"https://twitter.com/competitor2",
"https://twitter.com/competitor3"
]
}
viral_scoreScore post text or concepts for virality potential (0-100). Identifies emotional triggers, shareability factors, and provides improvement suggestions with platform-specific optimization tips.
Input:
{
"text": "Stop scrolling. Here are 5 things I wish I knew before starting my SaaS business:\n\n1. Your first 100 users matter more than your next 10,000\n2. Ship weekly, not monthly\n3. Talk to users every single day\n4. Pricing is a feature\n5. Distribution > Product\n\nWhich one resonates most?",
"platform": "linkedin"
}
| Platform | Profile Analysis | Hashtag Research | Content Calendar | Competitor Analysis |
|---|---|---|---|---|
| Twitter/X | Yes | Yes | Yes | Yes |
| Yes | Yes | Yes | Yes | |
| YouTube | Yes | Yes | Yes | Yes |
| Yes | Yes | Yes | Yes | |
| TikTok | Yes | Yes | Yes | Yes |
The server uses web scraping (basic HTML fetch + parsing) for publicly available data. No API keys or social media account connections required.
When live scraping is blocked (common with social media sites that require JavaScript rendering), the server falls back to intelligent estimation based on handle heuristics and platform benchmarks.
This makes the server:
MIT
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